Estimation of Petrophysical Properties Using Linear Programming Sparse Spike Inversion and Deep Feed-Forward Neural Network Techniques Over F3 Block, Netherlands: A Case Study

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dc.contributor.authorSingh R.
dc.contributor.authorKushwaha P.K.
dc.contributor.authorMaurya S.P.
dc.contributor.authorRai P.
dc.date.accessioned2025-01-13T07:06:18Z
dc.date.available2025-01-13T07:06:18Z
dc.date.issued2024
dc.description.abstractIn this study, acoustic impedance (P-impedance) distribution in the subsurface of the F3 block, Netherlands is determined using the linear programming (l1-norm) sparse spike inversion (LPSSI) method. The objectives of the study are to characterize the sand channel and extract high-resolution subsurface rock features from the low-resolution seismic data. To estimate rock properties from seismic data, a variety of conventional post-stack seismic inversion techniques are available. However, the LPSSI technique is a reasonably quick and easy-to-compute subsurface model that can be employed for both quantitative and qualitative interpretation. The method is employed in two steps: first, composite traces close to well locations are retrieved and inverted for acoustic P-impedance, and then optimization of the LPSSI parameters is done using comparison with well log impedance. According to the analysis of the composite traces, the algorithm performs well and has a high average correlation (0.98). The F3 block seismic data are utilized in the second stage to estimate the distribution of acoustic impedance in the subsurface by�using the LPSSI method. A sand channel-like low impedance anomaly with a range of 3800�7400�m/s�g/cc is evident in the inverted acoustic impedance analysis at the 1380�1400�ms time interval. Then, using a deep feed-forward neural network (DFNN), many other crucial rock parameters, including porosity, density, and P-wave velocity, were estimated in the inter-well region to corroborate the sand channel. Following the analysis of these petrophysical properties, a high porosity zone (24�40%), low-density zone (1.9�2.02�g/cc), and low P-wave velocity zone (1700�2300�m/s) are present in the 1380�1400�ms time interval, which aligns with the low impedance zone and validates the presence of the sand channel. � The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
dc.identifier.doi10.1007/s00024-024-03439-7
dc.identifier.issn334553
dc.identifier.urihttps://dl.bhu.ac.in/ir/handle/123456789/2271
dc.language.isoen
dc.publisherBirkhauser
dc.subjectacoustic impedance
dc.subjectdeep learning
dc.subjectdensity
dc.subjectneural network
dc.subjectporosity
dc.subjectSeismic inversion
dc.titleEstimation of Petrophysical Properties Using Linear Programming Sparse Spike Inversion and Deep Feed-Forward Neural Network Techniques Over F3 Block, Netherlands: A Case Study
dc.typeArticle
journal.titlePure and Applied Geophysics
journalvolume.identifier.volume181

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